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Stochastic interventions based on propensity modification

From agricultural field trials to modern biomedicine, science advances by posing causal and counterfactual questions such as what would happen under a different action…

Nov 1, 2025

Semiparametric estimation for the mean ReLU

semiparametric

Bayesian

counterfactual

A simple setting for a nonregular inference problem

May 17, 2024

A semi-formal presentation of targeted minimum loss estimation (TMLE)

TMLE combines ideas from targeted learning and the efficient influence function to provide mutiply-robust and efficient estimation method for causal inference

Jan 8, 2024

Simulation task: recovering causal effects from post-treatment selection induced by missing outcome data

A simulation exercise on missing data, selection bias, causal inference and TMLE

Oct 15, 2023

Structure learning for downstream causal inference with missing outcome data

A set of ideas on how to leverage structure learning and graph uncertainty quantification for downstream causal inference with missing data mechanisms in the outcome variable

Sep 15, 2023

Uncertainty modeling and quantification for causal inference

causal inference

graphical models

structure learning

A theoretical introduction of UQ in causal inference

Sep 1, 2023

Simulation task: recovering causal effects from post-treatment selection induced by missing outcome data

A simulation exercise on missing data, selection bias, causal inference and TMLE

Aug 15, 2023

Recovering causal effects from post-treatment selection induced by missing outcome data

Solutions to the problem of effect recoverability from selection/missingness via regression adjustment and doubly-robust estimation

Aug 1, 2023

Recovering from selection bias with IPW methods

IPW

selection bias

On the consistency of IPW methods to recover causal effects from selection bias

Mar 1, 2023

Categories

Stochastic interventions based on propensity modification

Semiparametric estimation for the mean ReLU

A semi-formal presentation of targeted minimum loss estimation (TMLE)

Simulation task: recovering causal effects from post-treatment selection induced by missing outcome data

Structure learning for downstream causal inference with missing outcome data

Uncertainty modeling and quantification for causal inference

Simulation task: recovering causal effects from post-treatment selection induced by missing outcome data

Recovering causal effects from post-treatment selection induced by missing outcome data

Recovering from selection bias with IPW methods